Optimal steering control of automated guideway transit vehicle with random guideway irregularities

Abstract

Lateral acceleration at passenger location is one of the most dominant factors for the comfort level of passengers. In applying a new way of transportation system like automated guideway transit vehicle system, to reduce such acceleration is essential for acceptability. To decrease acceleration level, optimal steering control is applied to an automated guideway transit vehicle with random guideway irregularities, and the effects are illustrated in view of rms acceleration and power spectral density. The coupled vertical-lateral model of Airtrans vehicle now operated at Dallas/Fort Worth Regional Airport area is reduced to have only lateral motion, and a stochastic optimal regulator problem is formulated with this reduced model. Frequency domain analysis is done for passive system, and for both passive and optimally-controlled systems the actual operating situations are simulated to yield time responses. Normally-distributed random numbers generated as to fit given statistics are used to simulate random processes. Optimal feedback gain is computed by Kalman-Engler method in a deterministic sense as to minimize given performance index. Measurement of all states is costly, or impossible, and often sensing noise in involved. Thus estimation is performed through Kalman filter, and control inputs are obtained as a feedback of this estimated states. Several results are demonstrated and compared together for two cases of weighting matrices with given guideway roughness coefficient. Desirable levels of rms output acceleration at passenger location and its power spectral density are achieved for optimally-controlled system.